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1 Improving Data Transmission Efficiency over Power Line Communication (PLC) System Using OFDM Charles U. Ndujiuba 1, Samuel N. John 1, Oladimeji Ogunseye 2 1 Electrical & Information Engineering, Covenant University, Ota, Nigeria. 2 Department of Electrical & Electronics Engineering, University of Lagos, Nigeria. Abstract Power lines were originally designed for AC power distribution at 50 Hz and 60 Hz, and the characteristics of this channel present some technical challenges for data transmission at these frequencies. This paper presents architecture for the physical layer of a PLC transceiver based on OFDM and the impact of a PLC transmission channel. A suitable and widely accepted PLC channel model is used for simulation purpose. In achieving the aim and objectives of this research work, simulation of PLC system was implemented using OFDM as the choice of modulation scheme. The results obtained compared with the theoretical QPSK result show that OFDM reduced the degrading effect of the PLC channel leading to a good performance. Furthermore, it is observed that at a signal level of 4dB, the simulated BER matches up with the required standard which is the theoretical QPSK value. At this signal level of 4dB, the theoretical and simulated BER graphs converge. This point gives the minimum BER tolerance of 10-2 that is acceptable for data transmission over PLC. Keywords: OFDM, PLC, QPSK, BER INTRODUCTION Power Line Communication (PLC) certainly is a cheap way to communicate, since no new wires are required, offering an existing last mile infrastructure [1]. The use of power lines which were originally designed for AC power distribution at 50 Hz and 60 Hz, present some technical challenges for data transmission at these frequencies. OFDM is now widely used as the most favorable modulation scheme for a severe communication environment such as the PLC channel [1]. The characteristics of this channel introduce the effect of noise, attenuation and multipath propagation which are the major challenges in implementing a PLC system. The application of OFDM in PLC enhances good performance through high spectral efficiency, resilience to Radio Frequency (RF) interference, and lower multi-path distortion. OFDM modulation scheme is now widely adopted, owing to its robustness to selective fading multipath and different kinds of interference [8]. Unlike single carrier modulation, OFDM is a multicarrier modulation technique, which employs several carriers, within the allocated bandwidth, to convey the information from source to destination. Each carrier may employ one of the several available digital modulation techniques (BPSK, QPSK, QAM etc..,) or sometimes a combination [4][18]. OFDM is very effective for communication over channels with frequency selective fading (different frequency components of the signal experience different fading). OFDM mitigates against the problem by converting the entire frequency selective fading channel into small flat fading channels (as seen by the individual subcarriers) [3] [13]. The process of PLC entails the conversion of communication signal into a form that will permit its transmission through electrical network. This paper examines the design of the physical layer, data layer and the channel of transmission. The system is modeled, simulated and implemented using MATLAB and the impact of OFDM is measured in terms of Bit Error Rate (BER). The organization of the paper is as follows. Firstly, the channel model and the employed OFDM system design are described in section 2. Analysis and simulation results are discussed in section 3. Finally, main conclusions are drawn in section 4. SYSTEM DESIGN Orthogonal Frequency Division Multiplexing (OFDM) is considered as the transmission scheme for Broadband over power lines (BPL) by most researchers. In OFDM, a highspeed serial data stream is split into a number of parallel slow data streams that are carried in multiple orthogonal subcarriers by means of Inverse Discrete Fourier Transform (IDFT). OFDM operation is carried out after the data is modulated using QPSK which is the input data stream. Subcarriers in the OFDM system are overlapping and orthogonal, which greatly improves the spectral efficiency necessary for a medium that has limited spectral capacity like the power line. In this way, OFDM can combat frequency selective attenuation and multipath propagation effect [3]. The discrete time OFDM signal can be expressed as: s(n) = 1 N 1 N k 0 S k e j2 nk N Where N is the number of sub-carriers, S k is a sequence of PSK or QAM symbols. In order to eliminate inter-channel interference (ICI) and inter-symbol interference (ISI), (1) 705

2 OFDM uses a cyclic prefix (CP) that is appended at the start of OFDM symbols [11]. The individual sub-streams are sent over N parallel sub-channels which are orthogonal to each other. Inverse fast Fourier transform (IFFT) on the OFDM transmitter side and Fast Fourier transform (FFT) FFT on the OFDM receiver side reduces system complexity, enabling OFDM to be easily implemented. Specifically, the OFDM Modulator System object modulates an input signal using orthogonal frequency division modulation. The output is a baseband representation of the modulated signal: where {X k} are data symbols, N is the number of subcarriers, and T is the OFDM symbol time. The data symbols, X k, are usually complex and can be from any modulation alphabet, e.g., QPSK, 16-QAM, or 64- QAM. Figure 1 shows an OFDM modulator. It consists of a bank of N complex modulators, where each corresponds to one OFDM subcarrier. (2) Figure 1: OFDM Modulator There are a number of choices of parameters for OFDM system design, for consideration. They are: number of subcarriers, guard time, symbol duration, sub carrier spacing, and modulation type per sub carrier. The number of carriers in an OFDM system is not only limited by the available spectral bandwidth, but also by the IFFT size. A FFT length of 128 and cyclic prefix length of 32 is used in this design. Figure 2 shows the block diagram of the proposed OFDM based PLC system. The input signal bits undergo convolutional encoding and interleaving before being mapped into QPSK symbols. The resulting data stream undergoes OFDM Modulation procedure realized by IFFT. Figure 2. Block diagram of an OFDM based PLC System Zimmermann and Dostert [2] have proposed a practical channel model that is suitable for describing the transmission behavior of power line channels. The model is based on practical measurements of actual power line networks and is given by the channel transfer function: (3) Where N p is the number of multipath, c i and d i are the weighting factor and length of the i th path respectively. Frequency-dependant attenuation is modeled by the parameters a 0, a 1 and k. In the model, the first exponential represents attenuation in the PLC channel, whereas the second exponential, with the propagation speed v p, describes the echo scenario. The attenuation parameters for 15-path 706

3 model were obtained using physical measurements [2]. represents the weighting factor, the attenuation portion and used parameters are given in table 1. the delay portion. The Table 1. Parameters for 15-path PLC Channel Model Attenuation parameters k=1 a 0= 0 a 1= 7.8*10-10 v=3*10^8 Path parameters i C d/m The proposed channel model has two parts: background noise (I AWGN) modeled as AWGN with mean zero and variance, and the impulsive noise I impulse is given by: Where impulsive noise, and I impulse = (4) is the Poisson Process which is the arrival of mean zero and variance. is white Gaussian process with ANALYSIS AND SIMULATION RESULTS In order to evaluate the performance of the designed system illustrated by Figure 2, the model is simulated using MATLAB R2015a. Emphasis is placed on the channel characteristic, OFDM performance and BER graph. The input signal is a stream of binary data, and Quaternary Phase Shift Keying (QPSK) is the preferred method of digital modulation. The BER plot shown in Figure 6 gives the overall performance of the simulated system. The combined PLC channel function is modeled as given: Therefore, the received signal after transmission is expressed as: (5) (6) Effect of the PLC and AWGN channel The input data is shown below in Figure 3. It is a stream of data consisting of 96 binary digits. This represents the source into the system. It is encoded using convolutional encoder to aid against channel error, passed through an interleaver, QPSK and finally OFDM block. (7) 707

4 Figure 3. Input signal data The channel factor is a combined effect of PLC impulse noise and the AWGN The channel introduced distortion to the encoded and modulated transmitted data. The plot of the modulated signal that is passed through the channel and recovered at the channel output shows the level of distortion introduced by the PLC channel. The channel output is a noise like signal. Therefore, it is not difficult to determine the effect the noise has on the transmitted signal. The recovery responses of the system i.e. channel encoding and modulations, are measured against the ability to recover the original data from the distorted noisy signal introduced by the system. The diagram in Figure 4 shows the scatter plot of the noisy signal generated by passing the modulated data through the channel. Figure 4. Transmitted data through PLC channel and AWGN 708

5 The recovered signal output is given in Figure 5. It is the result gotten after the distorted signal is recovered using Fast. Fourier Transform (FFT), QPSK demodulation, interleaver and Viterbi decoder respectively. Figure 5. Recovered binary data PERFORMANCE RESULT USING BIT ERROR RATE (BER) GRAPH A visual comparison of the input and final output which are displayed above can be done but a more suitable approach is using the Bit Error Rate (BER). The measurement of the performance of the system is illustrated with the bit-error rate (BER). The biterr function in MATLAB is used to compare two sets of data and computes the number of bit errors and the bit error rate. The plot in Figure 6 clearly shows the comparison between the simulated BER result for the channel and the theoretical QPSK BER curve. It can be observed that as the value of SNR increases, the BER of the simulated PLC system decrease and approaches that of the theoretical QPSK BER. At a SNR of 4dB, the theoretical and simulated BER graphs converge. This point gives the minimum BER tolerance of 10-2 that is acceptable for data transmission over PLC. At a signal level of 4dB, the rate of convergence approaches zero. The rate of BER convergence of the simulated data is estimated below in table 2. Figure 6. BER graph comparing theoretical and simulated data 709

Available Online at www.ijcsmc.com International Journal of Computer Science and Mobile Computing A Monthly Journal of Computer Science and Information Technology IJCSMC, Vol. 5, Issue. 2, February 2016,

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